原理：
我们先把树按照水平方式摆开。从根节点开始（“Food”），然后他的左边写上1。然后按照树的顺序（从上到下）给“Fruit”的左边写上2。这样，你沿着树的边界走啊走（这就是“遍历”），然后同时在每个节点的左边和右边写上数字。最后，我们回到了根节点“Food”在右边写上18。下面是标上了数字的树，同时把遍历的顺序用箭头标出来了。
我们称这些数字为左值和右值（如，“Food”的左值是1，右值是18）。正如你所见，这些数字按时了每个节点之间的关系。因为“Red”有3和6两个值，所以，它是有拥有1-18值的“Food”节点的后续。同样的，我们可以推断所有左值大于2并且右值小于11的节点，都是有2-11的“Fruit” 节点的后续。这样，树的结构就通过左值和右值储存下来了。这种数遍整棵树算节点的方法叫做“改进前序遍历树”算法。
表结构设计：
常用的操作：
下面列出一些常用操作的SQL语句
返回完整的树（Retrieving a Full Tree）
SELECT node.name
FROM nested_category node, nested_category parent
WHERE node.lft BETWEEN parent.lft AND parent.rgt
AND parent.name = 'electronics'
ORDER BY node.lft
返回某结点的子树（Find the Immediate Subordinates of a Node）
SELECT V.*
FROM (SELECT node.name,
(COUNT(parent.name) - (AVG(sub_tree.depth) + 1)) depth
FROM nested_category node,
nested_category parent,
nested_category sub_parent,
(SELECT V.*
FROM (SELECT node.name, (COUNT(parent.name) - 1) depth
FROM nested_category node, nested_category parent
WHERE node.lft BETWEEN parent.lft AND parent.rgt
AND node.name = 'portable electronics'
GROUP BY node.name) V,
nested_category T
WHERE V.name = T.name
ORDER BY T.lft) sub_tree
WHERE node.lft BETWEEN parent.lft AND parent.rgt
AND node.lft BETWEEN sub_parent.lft AND sub_parent.rgt
AND sub_parent.name = sub_tree.name
GROUP BY node.name) V,
nested_category T
WHERE V.name = T.name
and V.depth <= 1
and V.depth > 0
ORDER BY T.Lft
返回某结点的祖谱路径（Retrieving a Single Path）
SELECT parent.name
FROM nested_category node, nested_category parent
WHERE node.lft BETWEEN parent.lft AND parent.rgt
AND node.name = 'flash'
ORDER BY node.lft
返回所有节点的深度（Finding the Depth of the Nodes）
SELECT V.*
FROM (SELECT node.name, (COUNT(parent.name) - 1) depth
FROM nested_category node, nested_category parent
WHERE node.lft BETWEEN parent.lft AND parent.rgt
GROUP BY node.name) V,
nested_category T
WHERE V.name = T.name
ORDER BY T.Lft
返回子树的深度（Depth of a Sub-Tree）
SELECT V.*
FROM (SELECT node.name,
(COUNT(parent.name) - (AVG(sub_tree.depth) + 1)) depth
FROM nested_category node,
nested_category parent,
nested_category sub_parent,
(SELECT V.*
FROM (SELECT node.name, (COUNT(parent.name) - 1) depth
FROM nested_category node, nested_category parent
WHERE node.lft BETWEEN parent.lft AND parent.rgt
AND node.name = 'portable electronics'
GROUP BY node.name) V,
nested_category T
WHERE V.name = T.name
ORDER BY T.lft) sub_tree
WHERE node.lft BETWEEN parent.lft AND parent.rgt
AND node.lft BETWEEN sub_parent.lft AND sub_parent.rgt
AND sub_parent.name = sub_tree.name
GROUP BY node.name) V,
nested_category T
WHERE V.name = T.name
ORDER BY T.Lft
返回所有的叶子节点（Finding all the Leaf Nodes）
SELECT name FROM nested_category WHERE rgt = lft + 1
插入节点（Adding New Nodes）
LOCK TABLE nested_category WRITE;
SELECT @myRight := rgt FROM nested_category WHERE name = 'TELEVISIONS';
UPDATE nested_category SET rgt = rgt + 2 WHERE rgt > @myRight;
UPDATE nested_category SET lft = lft + 2 WHERE lft > @myRight;
INSERT INTO nested_category
(name, lft, rgt)
VALUES
('GAME CONSOLES', @myRight + 1, @myRight + 2);
UNLOCK TABLES;
删除节点（Deleting Nodes）
LOCK TABLE nested_category WRITE;
SELECT @myLeft := lft, @myRight := rgt, @myWidth := rgt - lft + 1
FROM nested_category
WHERE name = 'GAME CONSOLES';
DELETE FROM nested_category WHERE lft BETWEEN @myLeft AND @myRight;
UPDATE nested_category SET rgt = rgt - @myWidth WHERE rgt > @myRight;
UPDATE nested_category SET lft = lft - @myWidth WHERE lft > @myRight;
UNLOCK TABLES;
